Introduction: Documents are everywhere—PDFs, Word files, scanned images, spreadsheets. Extracting structured information from unstructured documents is one of the most valuable LLM applications. This guide covers building document processing pipelines: extracting text from various formats, chunking strategies for long documents, processing with LLMs for extraction and summarization, and handling edge cases like tables, images, and […]
Read more →Category: Technology Engineering
Technology Engineering
Building AI Agents with Tool Use: From ReAct to Production Systems
Introduction: AI agents represent the next evolution beyond simple chatbots—they can reason about problems, break them into steps, use external tools, and iterate until they achieve a goal. Unlike traditional LLM applications that respond to a single prompt, agents maintain state, make decisions, and take actions in the real world. The key innovation is tool […]
Read more →Token Management for LLM Applications: Counting, Budgeting, and Cost Control
Introduction: Token management is critical for LLM applications—tokens directly impact cost, latency, and whether your prompt fits within context limits. Understanding how to count tokens accurately, truncate context intelligently, and allocate token budgets across different parts of your prompt separates amateur implementations from production-ready systems. This guide covers practical token management: counting with tiktoken, smart […]
Read more →Building LLM-Powered CLI Tools: From Terminal to AI Assistant
Introduction: Command-line tools are the developer’s natural habitat. Adding LLM capabilities to CLI tools creates powerful utilities for code generation, documentation, data transformation, and automation. Unlike web apps, CLI tools are fast to build, easy to integrate into existing workflows, and perfect for power users who live in the terminal. This guide covers building production-quality […]
Read more →Multi-Modal AI: Advanced Vision, Audio, and Multi-Modal RAG (Part 2 of 2)
Introduction: Multi-modal AI combines text, images, audio, and video understanding in a single model. GPT-4V, Claude 3, and Gemini can analyze images, extract text from screenshots, understand charts, and reason about visual content. This guide covers building multi-modal applications: image analysis and description, document understanding with vision, combining OCR with LLM reasoning, audio transcription and […]
Read more →Context Window Management: Token Budgets, Prioritization, and Compression
Introduction: Context windows define how much information an LLM can process at once—from 4K tokens in older models to 128K+ in modern ones. Effective context management means fitting the most relevant information within these limits while leaving room for generation. This guide covers practical context window strategies: token counting and budget allocation, content prioritization, compression […]
Read more →